<h2>DESCRIPTION</h2>

<em>i.evapo.time</em> (i.evapo.time_integration) integrates ETa in time following a
reference ET (typically) from a set of meteorological stations dataset.

Inputs:
<ul>
<li> ETa images
<li> ETa images DOY (Day of Year)
<li> ETo images
<li> ETo DOYmin as a single value 
</ul>

Method:
<ol>
<li> each ETa pixel is divided by the same day ETo and become ETrF
<li> each ETrF pixel is multiplied by the ETo sum for the representative days
<li> Sum all n temporal [ETrF*ETo_sum] pixels to make a summed(ET) in [DOYmin;DOYmax]
</ol>

representative days calculation:
let assume i belongs to range [DOYmin;DOYmax]

<div class="code"><pre>
DOYbeforeETa[i] = ( DOYofETa[i] - DOYofETa[i-1] ) / 2
DOYafterETa[i] = ( DOYofETa[i+1] - DOYofETa[i] ) / 2
</pre></div>

<h2>NOTES</h2>

ETo images preparation:
If you only have one meteorological station data set, the easiest way is:

<div class="code"><pre>
n=0
for ETo_val in Eto[1] Eto[2] ...
do
	r.mapcalc "eto$n = $ETo_val" 
	`expr n = n + 1`
done
</pre></div>

with Eto[1], Eto[2], etc being a simple copy and paste from your data file
of all ETo values separated by an empty space from each other.
<p>
If you have several meteorological stations data, then you need to grid
them by generating Thiessen polygons or using different interpolation methods
for each day.
<p>
For multi-year calculations, just continue incrementing DOY values above
366, it will continue working, up to maximum input of 400 satellite images.

<h2>SEE ALSO</h2>

<em>
<a href="i.eb.eta.html">i.eb.eta</a>,
<a href="i.evapo.mh.html">i.evapo.mh</a>,
<a href="i.evapo.pt.html">i.evapo.pt</a>,
<a href="i.evapo.pm.html">i.evapo.pm</a>,
<a href="r.sun.html">r.sun</a>
</em>


<h2>AUTHOR</h2>
Yann Chemin, International Rice Research Institute, The Philippines

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